Triple
T9414379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudy Law |
E226977
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Sophia Law |
E171647
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sophia Law | Statement: [Rudy Law, sibling, Sophia Law]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sophia Law Context triple: [Rudy Law, sibling, Sophia Law]
-
A.
Sophia Law
chosen
Sophia Law is a British celebrity child known as one of actor Jude Law’s daughters.
-
B.
Maggie Law
Maggie Law is a member of the Law family, related to British model and actor Rafferty Law and connected to the wider circle of the actor Jude Law’s relatives.
-
C.
Janet Lam
Janet Lam is known as the wife of John Lee Ka-chiu, the Chief Executive of Hong Kong.
-
D.
Hilary Tsui
Hilary Tsui is a Hong Kong actress, fashion icon, and designer best known for her work in film and her influential street-style presence in the local fashion scene.
-
E.
Yvonne Szeto
Yvonne Szeto is a prominent architect and partner at the international architecture firm Pei Cobb Freed & Partners, known for her work on major cultural and institutional projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c7bd648190b17f082883c98239 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107b63cf48190a072e3434a7b85a8 |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:47 p.m.